Presented By O'Reilly and Cloudera
Make Data Work
March 13–14, 2017: Training
March 14–16, 2017: Tutorials & Conference
San Jose, CA
Alexander Ulanov

Alexander Ulanov
Senior Research Engineer, Hewlett Packard Labs

Website

Alexander Ulanov is a senior researcher at Hewlett Packard Labs, where he focuses his research on machine learning on a large scale. Currently, Alexander works on deep learning and graphical models. He has made several contributions to Apache Spark; in particular, he implemented the multilayer perceptron classifier. Previously, he worked on text mining, classification and recommender systems, and their real-world applications. Alexander holds a PhD in mathematical modeling from the Russian Academy of Sciences.

Sessions

2:40pm3:20pm Thursday, March 16, 2017
Platform Security and Cybersecurity, Spark & beyond
Location: LL21 C/D Level: Advanced
Secondary topics:  Hardcore Data Science
Alexander Ulanov (Hewlett Packard Labs), Manish Marwah (Hewlett Packard Labs)
Alexander Ulanov and Manish Marwah explain how they implemented a scalable version of loopy belief propagation (BP) for Apache Spark, applying BP to large web-crawl data to infer the probability of websites to be malicious. Applications of BP include fraud detection, malware detection, computer vision, and customer retention. Read more.